Genome-­wide scan of pulmonary phenotypes on local ancestry ⟶ genes interacting with smoking

Andrey Ziyatdinov, PostDoctoral Fellow at HSPH

September 27, 2017
Statistical Genetics Meeting
Channing Division of Network Medicine

Outline

  • Background and projects goals
  • Interaction model on local ancestry
  • Association results
  • Post-association analysis

Admixed genome

Leaveraging ancestry information

COPDGene African Americans (AA) dataset

  • 3.3K African Americans from the COPDGene project
  • 7 quantitative & 1 binary outcomes
    • FEV1/FEV1pp, FVC/FVCpp, FEV1_FVC, pctEmph_Slicer, TLCpp, finalGold
  • binary exposures
    • SmokCigNow, CigPerDayNow > 15, CompletedSchool > 2

37K long (>10kb) local ancestry segments (Parker et al. 2014)

Project goals

  1. Prove the validity of approach: local ancestry → gene-by-environment interactions
  2. Follow-up the ancestry-based finding
    • SNPs: fine-mapping
    • Gene Expression and Methylation association analysis in gene candidate regions

The COPDGene data is appropriate, as the proportion of (global) African ancestry was shown to be associated with the risk of COPD

Outline

  • Background and projects goals
  • Interaction model on local ancestry
  • Association results
  • Post-association analysis

First association model

  • marginal effect: \(y \sim a_g + a_l\)
  • interaction effect: \(y \sim a_g + a_l + x_e + a_g * x_e + a_e * x_e\)

Confounding factors other that global ancestry \(a_g\):

  • trait-sepcific covariates, e.g.
    • FEV1 ~ Age + Age^2 + Gender + Height + PackYears + SmokCigNow
  • random effect on medical centers (\(\approx\) 5% of variance)
    • random effect of medical device for pctEmph_Slicer trait

This (marginal) model was used in (Parker et al. 2014).
Is it OK for interaction?

First QQ plots: marginal & interaction

Our approach to fix model misspecification

  1. Ancestry Relatedness Matrix (ARM) (Zaitlen et al. 2014)
  2. Another (EARM) for ancestry-by-exposure component (Sul et al. 2016)
  3. Modeling heteroskedasticity (Don’t depreciate exploratory plots!)
  4. Selection of smoking covariates
    • SmokCigNow + ATS_PackYears → Duration_Smoking + log_CigPerDaySmokAvg + SmokCigNow + SmokCigNow0_15 + SmokCigarNow

More details in our previous talk COPDGene African-Americans & QQ plots

Heteroskedasticity & Covariance Matrices

Results: Clean QQ plots (marginal)

Results: Nearly Clean QQ plots (interaction)

Outline

  • Background and projects goals
  • Interaction model on local ancestry
  • Association results
  • Post-association analysis

Ancestry-by-SmokCigNow (7 traits)

Zoom in Chr 11 (2 repetetive traits)

Multi-trait joined test (5 traits)

\(z = [z_1; z_2; \dots]^T \sim N(0, \Sigma)\)
under the null hypothesis

  • Estimate covariance pairs
    • truncated normal
    • threshold 2.5
  • Apply omnibus test

Omnibus test(5 traits)

Results: Genes

Bonferroni 0.05 / 37K = 1.4e-06

Ancestry segment: 11:12,332,105 - 12,394,102
Genes: PARVA, MICAL2, MICALCL, RASSF10, TEAD1

Trait Exposure z-score p-value
FEV1pp SmokCigNow 4.5 7.3e-06
FEV1_FVC SmokCigNow 3.9 1.1e-04
FEV1 SmokCigNow 3.8 1.4e-04

Ancestry segment: 2:238,819,792 - 238,904,351
Genes: TWIST2, HDAC4, MIR4440, MIR4441

Trait Exposure z-score p-value
FEV1 SmokCigNow0_15 4.2 2.6e-05
FEV1pp SmokCigNow0_15 4.1 4.9e-05
FVC SmokCigNow0_15 4.0 6.9e-05
FVCpp SmokCigNow0_15 3.7 2.5e-04

Outline

  • Background and projects goals
  • Interaction model on local ancestry
  • Association results
  • Post-association analysis

References

Parker et al. 2014. “Admixture mapping identifies a quantitative trait locus associated with FEV1/FVC in the COPDGene Study.” Genetic Epidemiology 38 (7): 652–59. doi:10.1002/gepi.21847.

Sul et al. 2016. “Accounting for Population Structure in Gene-by-Environment Interactions in Genome-Wide Association Studies Using Mixed Models.” PLoS Genetics 12 (3): e1005849. doi:10.1371/journal.pgen.1005849.

Zaitlen et al. 2014. “Leveraging population admixture to characterize the heritability of complex traits.” Nature Genetics 46 (12). Nature Publishing Group: 1356–62. doi:10.1038/ng.3139.